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BIOSTATISTICS EXPERT - FULLY REMOTE | UPTO $170/HR

mercor
Part-timesenior€120-170/hour

Job description

About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey . Position: Biostatistician Type: Contract Compensation: $120–$170/hour Location: US or Canada Commitment: 20–25 hours/week Role Responsibilities • Simulate raw patient-level data and transform it through SDTM and ADaM into TLF outputs. Ensure every figure reconciles back to its source. • Execute end-to-end analysis pipelines and component tasks. Design prompts, golden outputs, and rubrics to quantify the ability of an AI agent . • Convert an existing SAP into data transformations and outputs. Produce synthetic data that is realistic rather than contrived. • Work independently and asynchronously to meet deadlines. Improve AI model performance through rigorous data analysis. • Collaborate with subject matter experts to ensure consistency, relevance, and coverage across datasets. Qualifications Must-Have • 5+ years of experience required; 10-25 years preferred. • MS in biostatistics or statistics required. • Hands-on experience across the SDTM , ADaM , and TLF layers of pre-market (Phases 1-3) trials. Preferred • PhD in biostatistics or statistics. • Availability for 30+ hours/week . Compensation & Legal • Hourly contractor Application Process (Takes 20–30 mins to complete) • Upload resume • AI interview based on your resume • Submit form Resources & Support • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome • For any help or support, reach out to: support@mercor.com PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Skills

SDTMADaMTLFSAPAI agentdata transformationssynthetic datapatient-level dataend-to-end analysis pipelines